/*
    * Licensed to the Apache Software Foundation (ASF) under one or more
    * contributor license agreements.  See the NOTICE file distributed with
    * this work for additional information regarding copyright ownership.
    * The ASF licenses this file to You under the Apache License, Version 2.0
    * (the "License"); you may not use this file except in compliance with
    * the License.  You may obtain a copy of the License at
    *
    *      https://www.apache.org/licenses/LICENSE-2.0
   *
   * Unless required by applicable law or agreed to in writing, software
   * distributed under the License is distributed on an "AS IS" BASIS,
   * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
   * See the License for the specific language governing permissions and
   * limitations under the License.
   */
  
  /*
   * This is not the original file distributed by the Apache Software Foundation
   * It has been modified by the Hipparchus project
   */
  package org.hipparchus.transform;
  
  import org.hipparchus.analysis.UnivariateFunction;
  import org.hipparchus.analysis.function.Sin;
  import org.hipparchus.analysis.function.Sinc;
  import org.hipparchus.exception.LocalizedCoreFormats;
  import org.hipparchus.exception.MathIllegalArgumentException;
  import org.hipparchus.exception.MathIllegalStateException;
  import org.hipparchus.exception.MathRuntimeException;
  import org.hipparchus.util.FastMath;
  import org.junit.jupiter.params.ParameterizedTest;
  import org.junit.jupiter.params.provider.MethodSource;
  
  import java.util.Arrays;
  import java.util.Collection;
  
  import static org.junit.jupiter.api.Assertions.assertEquals;
  import static org.junit.jupiter.api.Assertions.fail;
  
  /**
   * Test case for fast sine transformer.
   * <p>
   * FST algorithm is exact, the small tolerance number is used only
   * to account for round-off errors.
   *
   */
  public final class FastSineTransformerTest extends RealTransformerAbstractTest<DstNormalization> {
  
      private DstNormalization normalization;
  
      private int[] invalidDataSize;
  
      private double[] relativeTolerance;
  
      private int[] validDataSize;
  
      public void initFastSineTransformerTest(final DstNormalization normalization) {
          this.normalization = normalization;
          this.validDataSize = new int[] {
              1, 2, 4, 8, 16, 32, 64, 128
          };
          this.invalidDataSize = new int[] {
              129
          };
          this.relativeTolerance = new double[] {
              1E-15, 1E-15, 1E-14, 1E-14, 1E-13, 1E-12, 1E-11, 1E-11
          };
      }
  
      /**
       * Returns an array containing {@code true, false} in order to check both
       * standard and orthogonal DSTs.
       *
       * @return an array of parameters for this parameterized test
       */
      public static Collection<Object[]> data() {
          final DstNormalization[] normalization = DstNormalization.values();
          final Object[][] data = new DstNormalization[normalization.length][1];
          for (int i = 0; i < normalization.length; i++) {
              data[i][0] = normalization[i];
          }
          return Arrays.asList(data);
      }
  
      /**
       * {@inheritDoc}
       *
       * Overriding the default implementation allows to ensure that the first
       * element of the data set is zero.
       */
      @Override
      double[] createRealData(final int n) {
          final double[] data = super.createRealData(n);
          data[0] = 0.0;
          return data;
      }
  
      @Override
     RealTransformer createRealTransformer() {
         return new FastSineTransformer(normalization);
     }
 
     @Override
     int getInvalidDataSize(final int i) {
         return invalidDataSize[i];
     }
 
     @Override
     int getNumberOfInvalidDataSizes() {
         return invalidDataSize.length;
     }
 
     @Override
     int getNumberOfValidDataSizes() {
         return validDataSize.length;
     }
 
     @Override
     double getRelativeTolerance(final int i) {
         return relativeTolerance[i];
     }
 
     @Override
     int getValidDataSize(final int i) {
         return validDataSize[i];
     }
 
     @Override
     UnivariateFunction getValidFunction() {
         return new Sinc();
     }
 
     @Override
     double getValidLowerBound() {
         return 0.0;
     }
 
     @Override
     double getValidUpperBound() {
         return FastMath.PI;
     }
 
     @Override
     double[] transform(final double[] x, final TransformType type) {
         final int n = x.length;
         final double[] y = new double[n];
         final double[] sin = new double[2 * n];
         for (int i = 0; i < sin.length; i++) {
             sin[i] = FastMath.sin(FastMath.PI * i / n);
         }
         for (int j = 0; j < n; j++) {
             double yj = 0.0;
             for (int i = 0; i < n; i++) {
                 yj += x[i] * sin[(i * j) % sin.length];
             }
             y[j] = yj;
         }
         final double s;
         if (type == TransformType.FORWARD) {
             if (normalization == DstNormalization.STANDARD_DST_I) {
                 s = 1.0;
             } else if (normalization == DstNormalization.ORTHOGONAL_DST_I) {
                 s = FastMath.sqrt(2.0 / n);
             } else {
                 throw new MathIllegalStateException(LocalizedCoreFormats.ILLEGAL_STATE);
             }
         } else if (type == TransformType.INVERSE) {
             if (normalization == DstNormalization.STANDARD_DST_I) {
                 s = 2.0 / n;
             } else if (normalization == DstNormalization.ORTHOGONAL_DST_I) {
                 s = FastMath.sqrt(2.0 / n);
             } else {
                 throw new MathIllegalStateException(LocalizedCoreFormats.ILLEGAL_STATE);
             }
         } else {
              // Should never occur. This clause is a safeguard in case other
              // types are used to TransformType (which should not be done).
             throw MathRuntimeException.createInternalError();
         }
         TransformUtils.scaleArray(y, s);
         return y;
     }
 
     @Override
     void init(DstNormalization normalization) {
         initFastSineTransformerTest(normalization);
     }
 
     /*
      * Additional tests.
      */
     @MethodSource("data")
     @ParameterizedTest
     void testTransformRealFirstElementNotZero(final DstNormalization normalization) {
         initFastSineTransformerTest(normalization);
         final TransformType[] type = TransformType.values();
         final double[] data = new double[] {
             1.0, 1.0, 1.0, 1.0
         };
         final RealTransformer transformer = createRealTransformer();
         for (int j = 0; j < type.length; j++) {
             try {
                 transformer.transform(data, type[j]);
                 fail(type[j].toString());
             } catch (MathIllegalArgumentException e) {
                 // Expected: do nothing
             }
         }
     }
 
     /*
      * Additional (legacy) tests.
      */
 
     /**
      * Test of transformer for the ad hoc data.
      */
     @MethodSource("data")
     @ParameterizedTest
     void testAdHocData(final DstNormalization normalization) {
         initFastSineTransformerTest(normalization);
         FastSineTransformer transformer;
         transformer = new FastSineTransformer(DstNormalization.STANDARD_DST_I);
         double[] result;
         double tolerance = 1E-12;
 
         double[] x = { 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 };
         double[] y = { 0.0, 20.1093579685034, -9.65685424949238,
                        5.98642305066196, -4.0, 2.67271455167720,
                       -1.65685424949238, 0.795649469518633 };
 
         result = transformer.transform(x, TransformType.FORWARD);
         for (int i = 0; i < result.length; i++) {
             assertEquals(y[i], result[i], tolerance);
         }
 
         result = transformer.transform(y, TransformType.INVERSE);
         for (int i = 0; i < result.length; i++) {
             assertEquals(x[i], result[i], tolerance);
         }
 
         TransformUtils.scaleArray(x, FastMath.sqrt(x.length / 2.0));
         transformer = new FastSineTransformer(DstNormalization.ORTHOGONAL_DST_I);
 
         result = transformer.transform(y, TransformType.FORWARD);
         for (int i = 0; i < result.length; i++) {
             assertEquals(x[i], result[i], tolerance);
         }
 
         result = transformer.transform(x, TransformType.INVERSE);
         for (int i = 0; i < result.length; i++) {
             assertEquals(y[i], result[i], tolerance);
         }
     }
 
     /**
      * Test of transformer for the sine function.
      */
     @MethodSource("data")
     @ParameterizedTest
     void testSinFunction(final DstNormalization normalization) {
         initFastSineTransformerTest(normalization);
         UnivariateFunction f = new Sin();
         FastSineTransformer transformer;
         transformer = new FastSineTransformer(DstNormalization.STANDARD_DST_I);
         double min;
         double max;
         double[] result;
         double tolerance = 1E-12;
         int N = 1 << 8;
 
         min = 0.0; max = 2.0 * FastMath.PI;
         result = transformer.transform(f, min, max, N, TransformType.FORWARD);
         assertEquals(N >> 1, result[2], tolerance);
         for (int i = 0; i < N; i += (i == 1 ? 2 : 1)) {
             assertEquals(0.0, result[i], tolerance);
         }
 
         min = -FastMath.PI; max = FastMath.PI;
         result = transformer.transform(f, min, max, N, TransformType.FORWARD);
         assertEquals(-(N >> 1), result[2], tolerance);
         for (int i = 0; i < N; i += (i == 1 ? 2 : 1)) {
             assertEquals(0.0, result[i], tolerance);
         }
     }
 
     /**
      * Test of parameters for the transformer.
      */
     @MethodSource("data")
     @ParameterizedTest
     void testParameters(final DstNormalization normalization) throws Exception {
         initFastSineTransformerTest(normalization);
         UnivariateFunction f = new Sin();
         FastSineTransformer transformer;
         transformer = new FastSineTransformer(DstNormalization.STANDARD_DST_I);
 
         try {
             // bad interval
             transformer.transform(f, 1, -1, 64, TransformType.FORWARD);
             fail("Expecting MathIllegalArgumentException - bad interval");
         } catch (MathIllegalArgumentException ex) {
             // expected
         }
         try {
             // bad samples number
             transformer.transform(f, -1, 1, 0, TransformType.FORWARD);
             fail("Expecting MathIllegalArgumentException - bad samples number");
         } catch (MathIllegalArgumentException ex) {
             // expected
         }
         try {
             // bad samples number
             transformer.transform(f, -1, 1, 100, TransformType.FORWARD);
             fail("Expecting MathIllegalArgumentException - bad samples number");
         } catch (MathIllegalArgumentException ex) {
             // expected
         }
     }
 }